39 citations · 84 across the 9 of their papers we have counts for
8 papers · 1 filter
On mean-square boundedness of stochastic linear systems with quantized observations
Debasish Chatterjee, Peter Hokayem, Federico Ramponi +1
We propose a procedure to design a state-quantizer with finitely many bins for a marginally stable stochastic linear system evolving in , and a bounded policy based on the re…
Stochastic receding horizon control with output feedback and bounded control inputs
Peter Hokayem, Eugenio Cinquemani, Debasish Chatterjee +2
We provide a solution to the problem of receding horizon control for stochastic discrete-time systems with bounded control inputs and imperfect state measurements. For a suitable c…
On the well-posedness of multivariate spectrum approximation and convergence of high-resolution spectral estimators
Federico Ramponi, Augusto Ferrante, Michele Pavon
In this paper, we establish the well-posedness of the generalized moment problems recently studied by Byrnes-Georgiou-Lindquist and coworkers, and by Ferrante-Pavon-Ramponi. We the…
On the convergence of an efficient algorithm for Kullback-Leibler approximation of spectral densities
Augusto Ferrante, Federico Ramponi, Francesco Ticozzi
This paper deals with a method for the approximation of a spectral density function among the solutions of a generalized moment problem a` la Byrnes/Georgiou/Lindquist. The approxi…
On the connections between PCTL and Dynamic Programming
Federico Ramponi, Debasish Chatterjee, Sean Summers +1
Probabilistic Computation Tree Logic (PCTL) is a well-known modal logic which has become a standard for expressing temporal properties of finite-state Markov chains in the context…
Attaining mean square boundedness of a marginally stable noisy linear system with a bounded control input
Federico Ramponi, Debasish Chatterjee, Andreas Milias-Argeitis +2
We construct control policies that ensure bounded variance of a noisy marginally stable linear system in closed-loop. It is assumed that the noise sequence is a mutually independen…